R Basic

In a real-life dataset, the last row may contain metadata, summaries, footnotes, or unwanted rows that are not needed for data analysis. That’s why we need to clean the data. Data cleaning requires removing unnecessary rows from the data frame for data accuracy and integrity. We have already seen how to remove the first row … Read more

When we attempt to remove the first row of a data frame, we are essentially selecting all the rows except for the first one. This means we are excluding the first row and retrieving all other rows in the data frame. DataFrames are like tables with rows and columns. To remove rows, you can use … Read more

To grow the list, you can add an element (numeric value, character vectors, other lists, data frames, or functions) at whichever position you like. You can add a single element, multiple elements, or a list as an element. The final way depends on the user’s intention. Here are five ways to append an element to … Read more

Duplicate elements in a vector means those elements appear more than once. Duplicates can skew the data analysis and lead to inaccurate results. Removing them leads to more reliable insights. In R, unique() and subsetting with !duplicated() are efficient ways to remove duplicates. Method 1: Using unique() The unique() function is a one-step quick solution … Read more

Before executing an operation on an object, it is advisable to check its length, as this helps prevent potential errors. Some operations require an object to be of the same length. It ensures that an object has the expected number of elements. The length() function is used to set or get the length of vectors … Read more

Rounding is a process of approximating a number to a shorter, simpler, and more interpretable value while retaining its closeness to the original value. For example, if you are working in the finance division, you often publish a research report on the economy, where numbers in reports often round to 2 decimal points. Here are … Read more

For string operations like comparing strings, data standardization, formatting output, or input validation, we may want to convert the input to uppercase (or lowercase, depending on the situation) to ensure consistency and prevent errors caused by inconsistent capitalization. The toupper() function converts a string to an upper case. It accepts an input string and converts … Read more

The names() function in R gets or sets the names of objects such as vectors, lists, or data frames. If you are using it to fetch the name, it will return a character vector containing the names assigned to its elements or columns. Syntax names(obj) # To get names names(obj) <- value # To set names Parameters Name Value … Read more

When you convert a list to a matrix, you are essentially taking the elements of a list and rearranging them into a two-dimensional structure with rows and columns. To convert a list to the matrix in R, use the matrix() function and pass the unlist() function as an argument. The unlist() function flattens a list into a … Read more

If you are working with multidimensional data in R, you should explore Arrays. Arrays are designed to store data in more than two dimensions and represent complex data structures. The as.array() function attempts to coerce the input object into an array structure. It handles various input types, including vectors, lists, data frames, etc. Syntax as.array(input_obj, … Read more